1. Field of the Invention
This invention relates generally to apparatus and methods for measuring certain properties of energy-absorbing materials such as wood products, including wood-adhesive composite products, and metals, plastic, and concrete products. More specifically, the invention relates to an automated apparatus and method for measuring stiffness, or modulus of elasticity (MOE), and strength, or maximum stress at failure (MOR), of wood and related products, and for identifying such products in conjunction with measured values of parameters developed by the invention.
2. Description of Prior Art
Typically, the market value of wood products, such as pre-cut lumber products, is determined by classifying or grading the products according to established grading rules and procedures. In the mid-1920's, visual grading criteria were adopted for grading wood products in terms of their engineering properties, such as elasticity and strength under flexure, tension, and compression. The criteria adopted have come to be known as Visual Stress Grading Rules. The Visual Stress Grading Rules, which are widely used throughout the United States, are based on the visual inspection of wood products for certain predetermined, visually observable characteristics such as knots, warp, and the like. Under the Visual Grading Rules, trained operators or graders visually inspect the wood products and assign grade classifications thereto based on their judgment concerning the engineering properties of the products as a function of the visual criteria. The grades assigned by the operators are verified statistically by reference to past structural experience and laboratory testing of similar products.
In the 1960's, the first lumber grading machines designed to mechanically test individual pieces of pre-cut lumber non-destructively in flexure were introduced. The process of automatically grading individual pieces of lumber non-destructively in flexure by machine has become known as Machine Stress Rating (MSR) and lumber graded by such machines is commonly referred to as MSR lumber. Presently, there are estimated to be between 20 and 30 MSR grading installations in the United States. Unlike visually graded products, lumber grading machines typically grade MSR products automatically by actually measuring a selected parameter of the products under flexure, such as resistance to flexure, and relating the parameter to a selected engineering property. At present, structural MSR lumber is classified on the basis of a single measured parameter: stiffness in flexure or modulus of elasticity (MOE). From the measured MOE, strength values, e.g., modulus of rupture (MOR), are often assigned in accordance with a statistical correlation between stiffness and strength for similar destructively tested lumber samples.
Other prior art grading or classification machines have also been developed. Such machines operate on a variety of principles including inducing and measuring RF or microwave energy signals in the lumber and inducing stress waves and measuring the velocity or acceleration thereof. Similarly to the known MSR machines, these machines do not individually calculate selected physical parameters such as MOE and MOR directly and independently for each piece of lumber. In addition, such machines are typically not suitable for use in applications requiring high speed operation such as in the production line of a typical lumber mill.
The present invention seeks to provide an automated material classification apparatus and method for speedily and accurately determining selected physical parameters or properties of wood products particularly, and of other energy absorbing materials such as plastic, concrete, and metal, in general.
A significant feature and advantage of the apparatus and method of the invention is the ability to accurately calculate multiple selected physical parameters or properties of the material to be classified (such as MOE and MOR) individually and independently for each and every piece of the material.
Another significant feature and advantage of the apparatus and method of the invention is the ability to individually test each piece of material, analyze the results, and calculate the selected physical parameters at sufficiently high rates of speed to enable operation of the invention in the production line of a typical lumber mill.
Still another significant feature and advantage of the apparatus and method of the invention is the ability to test and classify the material without subjecting the material to physical deformation which may result in structural damage.
Other significant features and advantages are also provided and will become apparent from the detailed description and illustration of a presently preferred embodiment of the automated material classification apparatus and method set forth below.